Recent research has shown that usage of the radio spectrum is often fairly inefficient. One key factor in this is the current spectrum licensing system. That is, some part of the radio spectrum is licensed to a party, such as an operator of a radio communications system, who is given an exclusive right to use this part of the radio spectrum. For example, even though significant parts of the useful spectrum is licensed, several measurements (see, e.g. T. Erpek, K. Steadman, D. Jones, “Spectrum Occupancy Measurements: Dublin, Ireland, Collected On Apr. 16-18, 2007”, Shared Spectrum Company Report, 2007) indicate that some parts of this spectrum are highly underutilized. Therefore, a more flexible use of the radio spectrum has become a research intensive subject within which the aim is at optimizing, i.e. maximizing, the usage of the available radio spectrum. One approach pursued in regulations has been to license spectrum to a licensee (primary user), while at the same time allowing the licensed frequency band to be used by other users (secondary users) under the condition that they do not introduce harmful interference to the system operation of the primary user. Another approach under discussion is to have completely unlicensed spectrum, which has to be shared with equal right among many users.
New notions and terminologies have been developed in the effort to introduce a more flexible and efficient use of the radio spectrum.
One new term is Dynamic Spectrum Access, which describes spectrum access where radio units are not limited to using only a specific spectrum band (such as their licensed spectrum), but rather adapt the spectrum they use depending on conditions such as estimated throughput and latency requirements, spectrum availability etc. For instance, a cellular system suffering from high load in its own licensed spectrum could dynamically access spectral bands owned by some other licensee to temporarily increase its throughput, as long as it does not cause unacceptable interference to the primary system, or a network of communicating nodes may change its operating frequency depending on current spectral conditions. Potentially, dynamic spectrum access can enable more efficient use of the limited resource that radio spectrum is. This is because several systems then share the same resources such that when one system requires only a small amount of spectrum, other systems experiencing higher loads can utilize a greater bandwidth.
Another important notion is spectrum-on-demand, which means that radio nodes only operate as unlicensed (or secondary) users in a spectral band when triggered to do so. One reason for the radio nodes to initiate communication over unlicensed frequency bands could be that a licensed frequency band (if any) can not fulfill desired needs. Such events may occur, e.g., during peak hours at central stations, during special events such as concerts or sport events, or when several users in the same cell each demand a high bandwidth.
The spectrum-on-demand scenario usually looks slightly different depending upon the structure of the network, which may be both centralized and decentralized (autonomous).
A centralized network has a main (or central) node which has a controlling function over the network. Examples of centralized networks are the common cellular networks employed today for mobile communication, in which the main node (typically a base station (BS)) handles all communication with other nodes (user equipments UEs)) within a cell. Another example of a centralized network is an ad hoc network in which a master node (a function which may be given and handed over to any node in the network) has a regulating function over the other nodes.
In a decentralized network, all nodes are essentially equal (i.e. no node can control the operation of another node) and operate and communicate autonomously. Spectrum use is performed according to predetermined rules, or etiquette. If a node experiences an increased bandwidth demand, it can increase its use of a shared spectrum, if neighbouring nodes are willing to reduce their spectrum use. Alternatively the node can try to detect and access unused spectrum (which does not necessarily have to be shared with the other nodes) to meet the demand.
A concept, which relates to both centralized and decentralized networks (as well as to Dynamic Spectrum Access in general), is so-called spectrum sensing (sensing hereinafter). Sensing is the act of determining, by monitoring radio transmissions, whether e.g. a particular spectrum band is currently at least in part free for use. That is, sensing is a way of finding spectrum opportunities (e.g. various forms of radio resources), which may be accessed in a dynamic, and possibly secondary, manner. A device which takes part in the sensing is usually referred to as a sensor. Various network nodes, such as user equipments and base stations, may act as sensors. Since spectrum opportunities which are identified by sensing can be viewed as somewhat unreliable, they may be used for transmissions that are considered to be non time-critical.
It has been shown, e.g. in A. Ghasemi, E. S. Sousa, “Opportunistic Spectrum Access in Fading Channels Through Collaborative Sensing,” Journal of Communications, vol. 2, no. 2, pp. 71-82, March 2007, that several sensors which experience, at least to some extent, uncorrelated fading (with respect to the possible signals to which the sensing is applied) are required for high reliability. This is because a single sensor may be in a deep fade, which makes it virtually impossible to detect a current usage of spectrum resources. Therefore, it is often advocated that sensing should be performed in a cooperative manner involving a plurality of sensors.
Current research has been mainly focused on providing methods for detecting spectrum opportunities using cooperative sensing. Very little, however, has been done on how to select the sensors that will participate in the cooperative sensing. The concept of “distance spread” is treated in S. M. Mishra, A. Sahai, R. W. Brodersen, “Cooperative Sensing among Cognitive Radios”, IEEE Intl. Conf. on Communication, Vol. 4, June 2006 pp. 1658-1663. Here, sensing performance with respect to the number of sensors involved in cooperative sensing and the distance between the farthest sensors on a straight line is treated. The article shows that once a certain number of sensors are participating in the cooperative sensing, adding more sensors only improves the sensing performance marginally. A drawback, however, is that the geometry is mainly limited to a straight line.
A sensor performing spectrum sensing will of course deplete overall system resources. For example, the sensor will use power for its receiver and baseband circuitry and may thus reduce a battery life-time, and the sensing process will consume processing capacity. Also, a sensor normally needs to report its sensing result somehow, which requires additional communication resources. It is therefore desirable to use as few sensors as possible in the sensing, while still having a sufficient number for the sensing to be reliable. In this sense, the number of sensors to use is a trade-off between having a high reliability of the sensing and having a low or reasonable demand on resources, such as battery capacity, of the partaking sensors and transmission overhead in the communication system. Consequently, there exists a need to be able to select the sensors that participate in the cooperative sensing in an “optimal” manner which suitably balances these conflicting aspects.
One object of the present invention is therefore to overcome or at least mitigate at least one of the above-indicated difficulties.